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Building a SaaS product usually involves more than just writing code. You need market research, product planning, website design, and someone to catch problems before launch. I wanted to see if an entire workflow could happen inside one AI workspace. So I tested Teamily AI 2.0 by building LaunchPilot,...

52,140 次观看 • 3 天前 •via X (Twitter)

29 条评论

Blair Hayes 的头像
Blair Hayes3 天前

@Teamily_AI An AI team workflow for full SaaS launch is brilliant

Amelia | AI & Tech 的头像
Amelia | AI & Tech3 天前

@Teamily_AI Coordinated agents beat isolated answers for real work daily

Shara 的头像
Shara3 天前

@Teamily_AI Chaining research, planning, design and QA tests agent coordination well.

Leon Ai | tech & tools 的头像
Leon Ai | tech & tools3 天前

@Teamily_AI Coordinated agents beat single prompt answers

Aaliya 的头像
Aaliya3 天前

@Teamily_AI This is a good way to turn an idea into something people can actually use.

Aryan Rakib 的头像
Aryan Rakib3 天前

@Teamily_AI The shared context between agents is what really makes this workflow stand out.

Tanvir 的头像
Tanvir3 天前

@Teamily_AI This is a great example of AI-powered teamwork.

Aakash Kanojiya 的头像
Aakash Kanojiya3 天前

@Teamily_AI This is where multi-agent systems start making sense for real businesses.

JORDAN 的头像
JORDAN3 天前

@Teamily_AI Thanks for sharing this

Parul Gautam 的头像
Parul Gautam3 天前

@Teamily_AI AI is moving from answering questions to getting actual work done.

carmilla 的头像
carmilla3 天前

@Teamily_AI The storytelling makes the product reveal so much more engaging

Utkarsh Sharma 的头像
Utkarsh Sharma3 天前

@Teamily_AI Going from market research to a working website in one workspace is impressive.

Roshni 的头像
Roshni3 天前

@Teamily_AI So true! Coding is only half the battle when building a SaaS.

Alice The Ai Expert 的头像
Alice The Ai Expert3 天前

@Teamily_AI Teamily turns one idea into a full launch!

Manish Kumar Shah 的头像
Manish Kumar Shah3 天前

@Teamily_AI This could make early-stage product development much more efficient.

Waz 的头像
Waz3 天前

@Teamily_AI plant one wrong claim in the research notes and see if Review Agent stops it before the site goes out. that tells you if the review step is real.

Vini 的头像
Vini3 天前

@Teamily_AI Whole SaaS workflow, one agent.

ᗩshhh 的头像
ᗩshhh3 天前

@Teamily_AI appears pretty useful

Mujeeb Ahmed 的头像
Mujeeb Ahmed3 天前

@Teamily_AI Teamily 2.0 looks impressive!

Evia AI 的头像
Evia AI3 天前

@Teamily_AI Impressive demonstration showing seamless collaboration beautifully orchestrated

Md Riyazuddin 的头像
Md Riyazuddin3 天前

@Teamily_AI This is where AI workspaces get really interesting.

Vyera 的头像
Vyera3 天前

@Teamily_AI the catch problems before launch part is the one i'd trust ai with least tbh. curious how it did on that bit

Veyra | AI & Tech 的头像
Veyra | AI & Tech3 天前

@Teamily_AI One shared conversation keeping every agent aligned is huge

Hana Ai - Marketing Network 的头像
Hana Ai - Marketing Network3 天前

@Teamily_AI Coordinated agents beating solo prompts every time

Vincenzo Nudo 的头像
Vincenzo Nudo3 天前

@Teamily_AI A review agent on the same model tends to wave through what the research agent made up, since they share the same blind spots. I'd still check the market part against a few real calls with founders.

Mushfiq Sajib 的头像
Mushfiq Sajib3 天前

@Teamily_AI Having shared context across specialized agents makes revisions much easier than managing separate AI workflows.

E1ev3n. 的头像
E1ev3n.3 天前

@Teamily_AI My research notes lived in a different tab from my code within a day of starting a build last month. I keep the research and the build in the same place now and my launch checklist stopped losing items. I want to see whether one workspace holds up past the first week.

Fakhr 的头像
Fakhr3 天前

@Teamily_AI Turning idea into something exceptional! Here’s the way

Alex Ai | Tools & Updates 的头像
Alex Ai | Tools & Updates3 天前

@Teamily_AI AI agents building LaunchPilot from research to website is impressive

相关视频

The client cuts the budget in half. Your AI team invents a cheaper quote to make it fit. Would you catch it? 👀 I tested Teamily AI Teamily AI with a real-world project scenario: 📌 One landing page, 3 social posts, and a project plan. 💰 Budget: $2,000 ⏳ Deadline: 10 days Four specialist AI agents collaborated in one chat through a saved Loop. 🔍 Research flagged a critical issue: the enquiry form had no submission destination. 📋 Planning used that finding to scope the work. ⚠️ Review caught a scheduling conflict between Day 8 publishing and Day 9 approval. 💻 Webpage Developer turned the plan into a live project dashboard using Teamily Website Builder. Then I changed one requirement: “The budget is now $1,000. Day 10 stays.” I reran the saved Loop. The updated brief flowed through the team without repeatedly prompting every agent. But there was a problem. The team proposed a $750 “trimmed” page. Our fixed estimate was $900. That lower price had never been approved. I challenged it. The Review agent rejected the unsupported quote and sent the correction back to the developer. The final dashboard exposed the real situation: $1,600 in core work $1,000 available $600 budget gap Instead of pretending everything could fit, the workflow made the trade-offs visible. And I took it further. Inside Open Studio, I used a comment to ask the developer to make the budget gap and available options clearer at the top of the page. The developer refined the dashboard, and I could review the before-and-after result in the same workflow. That’s the difference between generating AI outputs and coordinating AI agents around a shared project. ✅ Multiple agents collaborating in one chat ✅ Saved workflows that adapt when requirements change ✅ Review that challenges unsupported assumptions ✅ Website editing through Open Studio ✅ Clearer decisions without rebuilding everything from scratch The real value of AI isn't making every answer look perfect. It's making problems, costs, and decisions impossible to ignore. The finished dashboard was built with Teamily Website Builder. 🔗 Explore the dashboard and compare the budget options: 🚀 Put your next project through the same test: #Ad #AI #AIAgents #AITools #WebsiteBuilder #Automation

Ryan Carter

121,889 次观看 • 10 天前